Object recognition using oriented model points
Computer Vision, Graphics, and Image Processing
The combinatorics of object recognition in cluttered environments using constrained search
Artificial Intelligence
Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
Region-based tracking using affine motion models in long image sequences
CVGIP: Image Understanding
Contour extraction of moving objects in complex outdoor scenes
International Journal of Computer Vision
VideoQ: an automated content based video search system using visual cues
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
Perception sensor for a mobile robot
Real-Time Imaging - Special issue on special-purpose architectures for real-time imaging, part 2
CAMP '97 Proceedings of the 1997 Computer Architectures for Machine Perception (CAMP '97)
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
On using the CAM concept for parametric curve extraction
IEEE Transactions on Image Processing
MPEG-4 standardized methods for the compression of arbitrarily shaped video objects
IEEE Transactions on Circuits and Systems for Video Technology
Real-time image segmentation on a GPU
Facing the multicore-challenge
Real-time image segmentation on a GPU
Facing the multicore-challenge
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Most of the emerging content-based multimedia technologies are based on efficient methods to solve machine early vision tasks. Among other tasks, object segmentation is perhaps the most important problem in single image processing. The solution of this problem is the key technology of the development of the majority of leading-edge interactive video communication technology and telepresence systems. The aim of this paper is to present a robust framework for real-time object segmentation and tracking in video sequences taken simultaneously from different perspectives. The other contribution of the paper is to present a new dedicated parallel hardware architecture. It's composed of a mixture of Digital Signal Processing (DSP) and Field Programmable Gate Array (FPGA) technologies and uses the Content Addressable Memory (CAM) as a main processing unit. Experimental results indicate that small amount of hardware can deliver real-time performance and high accuracy. This is an improvement over previous systems, where execution time of the second-order using a greater amount of hardware has been proposed.